Formation and evaluation of mechanism-based chemical categories for regulatory read-across assessment of repeated-dose toxicity: A case of hemolytic anemia

The aim of this study is to define chemical categories that can be applied to regulatory read-across assessments for repeated-dose toxicity, by classifying toxic substances based on their structures and mechanism of actions (MoAs). Hemolytic anemia, which often appears primarily, was examined as an example. An integrated database was constructed by collecting publicly available datasets on repeated-dose toxicity, in which 423 out of a total of 1518 chemicals were identified as capable of inducing hemolytic anemia. Subsequently, by grouping these chemicals based on their chemical structures and plausible MoAs on hemolytic substances, we identified the following categories: (i) anilines, (ii) nitrobenzenes, (iii) nitroanilines, (iv) dinitroanilines, (v) ethylene glycol alkyl ethers, (vi) hydroquinones, (vii) oximes, and (viii) hydrazines. In these categories, the toxicant and the measurable key events leading to hematotoxicity were identified, thereby allowing us to justify the categories and to discriminate the category substances. Moreover, toxicokinetics seems to critically affect the hemolytic levels of the category substances. Overall, the categories were validated through a comprehensive analysis of the collected information, while the utility was demonstrated by conducting a case study on the selected category. Further endeavors with this approach would attain categories for other organ toxicity endpoints.

Automated summary

The aim of this study is to define chemical categories for regulatory read-across assessments of repeated-dose toxicity by classifying toxic substances based on their structures and mechanisms of actions. Hemolytic anemia was examined as an example. Through an integrated database, 423 chemicals capable of inducing hemolytic anemia were identified and grouped into categories based on their structures and plausible mechanisms of actions. The identified categories were validated by comprehensive analysis and demonstrated utility through a case study.